1. We provide a comprehensive protocol for REvoDesign-assisted protein design. See the Design section for details.
2. We also provide complete molecular cloning and plasmid construction protocols.
3. We provide complete transformation protocols for Escherichia coli and Saccharomyces cerevisiae .
4. We also provide detailed instructions for using REvoDesign.
5. We provide specific extraction and analysis methods for lycopene and taxadiene-5-ol.
1. 3 Basics parts.See parts：https://2025.igem.wiki/ynnu-china/parts.
2. We provide a detailed design plan for the lycopene case and codon-optimized three heterologous genes for Saccharomyces cerevisiae.
3. We used REvoDesign to design mutant libraries of CarRP and T5αH.
4. We provide three compatible components, which are the wild type and two mutants of CarRP, a key enzyme in the heterologous biosynthesis pathway of lycopene.
5. All of our parts have also been uploaded to the iGEM Parts Library, please see the link below for details.
We developed a computational framework, REvoDesign, which integrates bioinformatics co-evolutionary analysis with structure-guided rational design to address the prevalent stability–activity trade-off of plant-derived enzymes in microbial hosts and to provide a versatile computational tool for the synthesis of high-value natural products. The framework leverages deep-learning–based structure prediction (AlphaFold3, DiffDock) to accurately identify design hotspots within catalytic pockets and on protein surfaces. Potential mutation sites and residue substitutions are systematically prioritized using reverse PSSM conservation profiling in combination with GREMLIN co-evolutionary matrices.
Building on these analyses, we introduce a long-range, cross-domain combinatorial strategy: activity-enhancing mutations are incorporated into catalytic pockets, while stabilizing mutations are selected on protein surfaces. Through synergistic integration of these distant modifications, the model enables simultaneous optimization of both activity and stability, thereby mitigating the risk of negative epistasis and overcoming the conventional bottleneck in protein engineering where activity improvements often compromise stability.
To minimize experimental validation costs, REvoDesign incorporates multidimensional energy screening, molecular dynamics simulations, sequence clustering, and Rosetta scoring to cross-filter and comprehensively evaluate preliminary mutation libraries. This process substantially reduces the number of variants required for testing while increasing the success rate of beneficial mutants. Beyond plant enzymes, the framework is broadly applicable to fungal and other natural enzymes, offering efficient optimization pathways across diverse structural and functional classes. In our iGEM project, REvoDesign enabled site-specific optimization and cross-domain combinatorial design of key metabolic enzymes, leading to enhanced target product synthesis and the identification of significantly improved variants under limited experimental conditions.
In summary, REvoDesign provides not only our iGEM team but also the wider synthetic biology community with a data-driven, modular, and iterative platform for enzyme optimization. By seamlessly integrating high-accuracy structure prediction, evolutionary information mining, and cross-domain combinatorial strategies, it establishes a new paradigm in enzyme engineering—characterized by reduced experimental burden, improved success rates, and broad applicability—thereby offering robust technological support for the future synthesis and industrial production of natural products.
REvoDesign is an open-source, data-driven, and structure-guided enzyme design software developed to accelerate protein engineering in synthetic biology. It integrates state-of-the-art computational modeling, evolutionary analysis, and rational design strategies into a unified and user-friendly platform, enabling iGEM teams and other researchers to generate stable and active enzyme variants with minimal experimental burden.
At its core, REvoDesign features a hybrid computational framework that combines deep-learning–based structure prediction tools (AlphaFold, RoseTTAFold, DiffDock) with evolutionary conservation and co-evolutionary analysis methods (PSSM, GREMLIN). This integration allows automatic identification of mutation hotspots in catalytic pockets and on protein surfaces, facilitating targeted enzyme engineering. Building on this foundation, the software incorporates a cross-region optimization engine, which supports the simultaneous design of active-site and surface mutations. By offering algorithms that balance stability and activity while mitigating negative epistasis, it provides flexible mutation constraints and customizable scoring functions to meet diverse design goals.
To further reduce the experimental burden, REvoDesign implements compact variant library generation, integrating multidimensional computational filters—including ΔΔG predictions, molecular dynamics simulations, and machine-learning models—alongside sequence clustering. This approach yields a small, high-confidence mutant library, significantly decreasing wet-lab screening requirements. The platform also offers a modular and intuitive graphical interface, developed in Python using PyQt5 and enhanced with a PyMOL plugin for three-dimensional visualization. The workflow is organized into logical tabs—Prepare → Mutate → Evaluate → Visualize → Interact—that align with the Design–Build–Test–Learn (DBTL) cycle. In addition, a "design recipe" configuration enables experiments to be saved, shared, and reproduced with ease.
Finally, REvoDesign is built on an open and extensible architecture, distributed as a GitHub package with pip-based "extras" installation for effortless tool management. Its modular design allows seamless integration of new algorithms, such as molecular docking and AI-driven protein design, without modifications to the core framework. Together, these features establish REvoDesign as a versatile, scalable, and accessible tool for advancing enzyme engineering in synthetic biology.
REvoDesign provides a ready-to-use computational platform for enzyme engineering, enabling iGEM teams to perform protein design even without high-performance computing resources or programming experience. By reducing experimental screening requirements, it significantly accelerates the Design–Build–Test–Learn cycle and promotes data-driven rational design. At the same time, as a community-driven and extensible framework, REvoDesign allows teams to integrate new modules and share design recipes, continuously advancing the development and innovation of synthetic biology software tools.
1.We have developed an IHP work framework and organized our research into three modules: (1) research on the demand for protein design tools and provision of technical support, (2) investigation of high-value plant-derived natural products, and (3) application and assessment of protein design tools. We have conducted focused research within these three modules.
2.Within our IHP investigation, we systematically analyzed the industrial and societal demands for heterologous synthesis of high-value plant natural products and identified a central bottleneck: the poor compatibility and low catalytic efficiency of plant-derived key enzymes in microbial systems. By integrating disease reports, policy documents, corporate annual reports, expert interviews, and survey data, we established a comprehensive framework that links public health concerns, industrial challenges, and scientific research needs. On this basis, we developed the REvo Design protein design tool and demonstrated its effectiveness in two representative cases: the Taxol biosynthetic enzyme T5αH and the carotenoid biosynthetic enzyme CarRP. Through in-depth engagement with enterprises and research teams, we not only received expert feedback to guide further tool refinement but also established industrial collaborations, thereby enhancing the project's feasibility and impact across scientific value, industrial application, and social responsibility.
3.Education: We visited Erjie Town Central Primary School in Jinning District, Kunming City, hoping to cultivate scientific thinking and sow the seeds of innovation in children through our science education. We also sought to promote the iGEM concept and synthetic biology concepts among undergraduate students at the School of Life Sciences at Yunnan Normal University. We also conducted REvo Design tool training within our synthetic biology team to put this knowledge into practice.
4. Through 27 rounds of social practice, expert interviews, and industry visits, we connected synthetic biology research with real industrial demands.Signed a tripartite strategic cooperation agreement with Hubei Meiqi Health Technology Co., Ltd. and the Agricultural Genomics Institute of CAAS(Chinese Academy of Agricultural Sciences) to translate research into pilot-scale production.Collected first-hand feedback from multiple research groups and companies to refine REvoDesign and improve its industrial applicability.